U
Unison GroupSingapore, Singapore
Data Engineering Manager - Big Data
Posted 7d agoData Engineer
At a glance
- Posted
- 22 October 2026
- Workplace
- Remote
- Type
- Contract
- Level
- Lead
- Country
- Singapore
- Skills named
- aws, azure, data pipeline, data warehouse, data migration, databricks, financial services, gcp
- Application form
- Workable
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Location:
Singapore
- Experience:
- 10+ years in Data Engineering, including hands-on Big Data expertise and team management
- Domain:
Banking / Financial Services preferred
- Key Responsibilities
- Lead and manage data engineering teams to design, develop, and deliver scalable enterprise data platforms and pipelines.
- Maintain strong hands-on expertise in Big Data technologies such as
- Hadoop, Spark, PySpark, Hive, Kafka, and distributed data processing
- Design and implement robust ETL/ELT pipelines, data ingestion frameworks, data transformation, and data integration solutions.
- Drive data engineering architecture, technical design, performance tuning, and optimization of large-scale data processing workloads.
- Manage data lake, data warehouse, and modern cloud-based data platform implementations.
- Work with cloud platforms such as AWS, Azure, or GCP and technologies such as Databricks, where applicable.
- Lead data quality, data governance, metadata management, security, and data reliability initiatives.
- Collaborate with solution architects, data architects, business stakeholders, and project managers to translate business requirements into technical solutions.
- Manage project delivery, resource allocation, technical reviews, risk mitigation, and delivery timelines.
- Mentor engineers, establish engineering best practices, and ensure high-quality, maintainable, and production-ready code.
Required Skills and Experience
10+ years of experience in data engineering, Big Data development, and enterprise data platforms.
Proven
- hands-on experience in Big Data technologies, with the ability to guide teams technically and troubleshoot complex engineering challenges.
- Strong proficiency in Python, PySpark, SQL, and distributed data processing frameworks.
- Experience building and managing complex data pipelines, ETL/ELT workflows, and large-scale data processing solutions.
- Demonstrated experience leading data engineering teams, managing deliverables, and driving technical execution.
- Strong understanding of data modelling, data architecture, performance optimization, and data platform scalability.
- Experience with cloud-based data engineering and modern data platforms is highly desirable.
- Excellent stakeholder management, communication, problem-solving, and leadership skills.
- Preferred:
- Experience in banking, financial services, regulatory reporting, risk analytics, or other data-intensive enterprise environments.
- Ideal Candidate:
- A technically strong Data Engineering Manager who combines practical Big Data development experience with proven people leadership, solution delivery, and the ability to guide engineers through complex data engineering challenges.